Fundamentals and Methods of Machine and Deep Learning

Fundamentals and Methods of Machine and Deep Learning
Author: Pradeep Singh
Publisher: John Wiley & Sons
Total Pages: 484
Release: 2022-03-02
Genre: Computers
ISBN: 1119821258

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FUNDAMENTALS AND METHODS OF MACHINE AND DEEP LEARNING The book provides a practical approach by explaining the concepts of machine learning and deep learning algorithms, evaluation of methodology advances, and algorithm demonstrations with applications. Over the past two decades, the field of machine learning and its subfield deep learning have played a main role in software applications development. Also, in recent research studies, they are regarded as one of the disruptive technologies that will transform our future life, business, and the global economy. The recent explosion of digital data in a wide variety of domains, including science, engineering, Internet of Things, biomedical, healthcare, and many business sectors, has declared the era of big data, which cannot be analysed by classical statistics but by the more modern, robust machine learning and deep learning techniques. Since machine learning learns from data rather than by programming hard-coded decision rules, an attempt is being made to use machine learning to make computers that are able to solve problems like human experts in the field. The goal of this book is to present a??practical approach by explaining the concepts of machine learning and deep learning algorithms with applications. Supervised machine learning algorithms, ensemble machine learning algorithms, feature selection, deep learning techniques, and their applications are discussed. Also included in the eighteen chapters is unique information which provides a clear understanding of concepts by using algorithms and case studies illustrated with applications of machine learning and deep learning in different domains, including disease prediction, software defect prediction, online television analysis, medical image processing, etc. Each of the chapters briefly described below provides both a chosen approach and its implementation. Audience Researchers and engineers in artificial intelligence, computer scientists as well as software developers.


Fundamentals and Methods of Machine and Deep Learning
Language: en
Pages: 484
Authors: Pradeep Singh
Categories: Computers
Type: BOOK - Published: 2022-03-02 - Publisher: John Wiley & Sons

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FUNDAMENTALS AND METHODS OF MACHINE AND DEEP LEARNING The book provides a practical approach by explaining the concepts of machine learning and deep learning al
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This book introduces basic machine learning concepts and applications for a broad audience that includes students, faculty, and industry practitioners. We begin
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With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that’s paving the way for modern m
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Pages: 801
Authors: Ian Goodfellow
Categories: Computers
Type: BOOK - Published: 2016-11-10 - Publisher: MIT Press

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An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and res
Machine Learning Fundamentals
Language: en
Pages: 423
Authors: Hui Jiang
Categories: Computers
Type: BOOK - Published: 2021-11-25 - Publisher: Cambridge University Press

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A coherent introduction to core concepts and deep learning techniques that are critical to academic research and real-world applications.